PAFway
PAFway quantifies pairwise associations between functional annotations within biological networks and pathways to elucidate functional relationships and regulatory interactions.
Key Features:
- Pairwise Association Estimation: Estimates pairwise associations between functional annotations across biological networks and pathways.
- Biological Insight Generation: Identifies whether genes with specific functions tend to influence or interact with genes bearing different functions, supporting inference of regulatory mechanisms.
- Visualization Capabilities: Produces heatmaps and network diagrams of biological functions to represent complex associations.
- Application to Model Organisms: Has been applied to an Arabidopsis thaliana gene network.
Scientific Applications:
- Dissection of Gene Regulatory Networks: Supports identification and interpretation of functional associations within complex gene regulatory networks.
- Systems Biology: Enables systems biology analyses by mapping functional relationships across pathways.
- Gene Regulation Studies: Aids studies of gene regulation by revealing associative influences among functionally annotated genes.
- Network Biology and Functional Genomics: Supports network biology and functional genomics by enabling analysis and visualization of functional associations across pathways.
Methodology:
Calculates pairwise associations between functional annotations derived from biological networks and pathways and applies statistical techniques to assess the strength and significance of these associations.
Topics
Details
- Tool Type:
- library
- Programming Languages:
- R
- Added:
- 1/18/2021
- Last Updated:
- 9/16/2021
Operations
Publications
Mahjoub M, Ezer D. PAFway: pairwise associations between functional annotations in biological networks and pathways. Bioinformatics. 2020;36(19):4963-4964. doi:10.1093/bioinformatics/btaa639. PMID:32678900. PMCID:PMC7750965.
PMID: 32678900
PMCID: PMC7750965
Funding: - Turing Research Fellowship under Engineering and Physical Sciences Research Council: TU/A/000017
- EPSRC/Biotechnology and Biological Sciences Research Council (BBSRC) Innovation Fellowship: EP/S001360/1
- United Kingdom Research and Innovation (UKRI)/Turing Research Strategic Priority Fund: R-SPES-107